Graph Theory based multicast caching for better energy saving in dense small cell networks
Safa Mrad, Soumaya Hamouda, Houria Rezig · 2017
Endowed with the potential of context-awareness and proactive networking, caching popular content files locally at the wireless edge is a promising way to handle the growing traffic demand in the next 5G networks. It also helps boost the spectral efficiency and reduce the energy consumption in the network. However, various factors affect the Energy Efficiency (EE) like power consumption, backhaul capacity, content popularity and cache capacity at the base stations. In this paper, we propose a new solution of multicast caching in dense small cell networks based on Graph Theory in order to enhance the EE in the system. More precisely, we identify the condition when a group of user can benefit from multicast caching at a lower energy cost. Special attention is also paid to the number of small base stations which are involved in the graph to ensure a tradeoff between EE and cache size. Numerical results show that multicast caching based on our proposed graph can save the energy consumption in presence of massive content demand as well as for an increasing number of cached files at the base stations.